The DOI matches its Crossref record; 38 of the 39 references it cites were found in a registry or an index.
Text messaging as an adjunct to CBT in low-income populations: A usability and feasibility pilot study.
Open accessAbstract
This article outlines the development and usability-feasibility testing of an automated text-messaging adjunct to cognitive- behavioral therapy (CBT) for depression in a public sector clinic serving low-income patients. The text-messaging adjunct is aimed at increasing homework adherence, improving self-awareness, and helping track patient progress. Daily text messages were sent to patients, inquiring about their mood. Additional daily messages corresponded to themes of a manualized group CBT intervention. These included (1) thought tracking (both positive and negative), (2) tracking of pleasant activities, (3) tracking of positive and negative contacts, and (4) tracking of physical well-being. We tested the adjunct in 2 CBT groups (1 English & 1 Spanish) consisting of 12 patients total during and after treatment. Participants responded at a rate of 65% to text messages, and they reported overall positive experiences. We propose that text messaging has the potential to improve mental health care broadly, and among low-income populations specifically, with cost-effective means.
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 source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Text messaging reminders have proven effective in increasing treatment adherence among POC community samples [54-56,63], including those in app-based mindfulness meditation studies [49].”
From App-Based Mindfulness Meditation for People of Color Who Experience Race-Related Stress: Protocol for a Randomized Controlled Trial (2022) · cites this paper as [56]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“Importantly, this engagement strategy is well tolerated by participants [56].”
From App-Based Mindfulness Meditation for People of Color Who Experience Race-Related Stress: Protocol for a Randomized Controlled Trial (2022) · cites this paper as [56]
In the citing paper
“and that receiving this text messaging adjunct increases attendance.”
From Ecological momentary interventions for depression and anxiety (2017) · cites this paper as Aguilera & Munoz, 2011
In the citing paper
“Indeed, EMIs have been used as an adjunct to therapy to increase homework adherence and reinforce therapeutic concepts in realworld settings.”
From Ecological momentary interventions for depression and anxiety (2017) · cites this paper as Aguilera & Munoz, 2011
In the citing paper
“evidence from other studies suggests that app adherence and, thus, efficacy might be improved by extending program prompts and psychoeducational messaging beyond the original 6-week intervention period and/or providing mobile-friendly prompts (eg, text messages and app notifications) in addition to the emails utilized here [65,90].”
From MoodHacker Mobile Web App With Email for Adults to Self-Manage Mild-to-Moderate Depression: Randomized Controlled Trial (2016) · cites this paper as [65]
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
Molecular Mechanisms of Depression: Perspectives on New Treatment Strategies
Lang, U. E., & Borgwardt, S. (2013) · Cellular Physiology and Biochemistry · doi:10.1159/000350094 · Cited by 8,526
Osterberg, L., & Blaschke, T. (2005) · New England Journal of Medicine · doi:10.1056/nejmra050100 · Cited by 7,974
Handbook of Psychotherapy and Behavior Change
Garfield, S. L., Bergin, A. E., & Dryden, W. (1987) · Journal of Cognitive Psychotherapy · doi:10.1891/0889-8391.1.4.264a · Cited by 3,998
The Prevalence of Comorbid Depression in Adults With Diabetes
Anderson, R. J., Freedland, K. E., Clouse, R. E., & Lustman, P. J. (2001) · Diabetes Care · doi:10.2337/diacare.24.6.1069 · Cited by 3,926
Kirk, J. M. W., MacDonald, A., Lavender, P., Dean, J. M., & Rubin, G. (2017) · Biomedicine Hub · doi:10.1159/000480347 · Cited by 3,902
Relation between working alliance and outcome in psychotherapy: A meta-analysis
Horvath, A. O., & Symonds, B. D. (1991) · Journal of Counseling Psychology · doi:10.1037/0022-0167.38.2.139 · Cited by 2,673
Unützer, J., Katon, W., Callahan, C. M., Williams, Jr., Hunkeler, E., Harpole, L., Hoffing, M., Della Penna, R. D., Noël, P. H., Lin, E. H. B., et al. (2002) · JAMA · doi:10.1001/jama.288.22.2836 · Cited by 2,405
Evidence-based health policy—lessons from the Global Burden of Disease Study
Murray, C. J. L., & Lopez, A. D. (1996) · Science · doi:10.1126/science.274.5288.740 · Cited by 2,178
Text messaging as a tool for behavior change in disease prevention and management
Cole-Lewis, H., & Kershaw, T. (2010) · Epidemiologic Reviews · doi:10.1093/epirev/mxq004 · Cited by 1,190 · cited 2×
“…reminders (Leong et al., 2006), medication reminders (Miloh et al., 2009), and health information ( Studies have shown initial efficacy for SMS as a tool to improve weight loss, increase smoking cessation, and reduce A1c levels in patients with diabetes (as noted in Cole-Lewis & Kershaw, 2010).”
MethodDisparity in Depression Treatment Among Racial and Ethnic Minority Populations in the United States
Alegría, M., Chatterji, P., Wells, K., Cao, Z., Chen, C.-N., Takeuchi, D., Jackson, J., & Meng, X.-L. (2008) · Psychiatric Services · doi:10.1176/ps.2008.59.11.1264 · Cited by 993
Depression and the risk for cardiovascular diseases: Systematic review and meta analysis
Van der Kooy, K., van Hout, H., Marwijk, H., Marten, H., Stehouwer, C., & Beekman, A. (2007) · International Journal of Geriatric Psychiatry · doi:10.1002/gps.1723 · Cited by 951
Alegria, M. M., CANINO, G. J., Ríos, R. E., Vera, M., Calderón, J., Rusch, D. B., & Ortega, A. N. (2002) · Psychiatric Services · doi:10.1176/appi.ps.53.12.1547 · Cited by 799
Rodgers, A., Corbett, T., Bramley, D., Riddell, T., Wills, M., Lin, R.-B., & Jones, M. (2005) · Tobacco Control · doi:10.1136/tc.2005.011577 · Cited by 732
A Text Message–Based Intervention for Weight Loss: Randomized Controlled Trial
Patrick, K., Raab, F., Adams, M. A., Dillon, L., Zabinski, M., Rock, C. L., Griswold, W. G., & Norman, G. J. (2009) · Journal of Medical Internet Research · doi:10.2196/jmir.1100 · Cited by 671
Research on client variables in psychotherapy.
Garfield, S. L. (1994) · Cited by 671
Franklin, V. L., Waller, A., Pagliari, C., & Greene, S. A. (2006) · Diabetic Medicine · doi:10.1111/j.1464-5491.2006.01989.x · Cited by 543
Comorbid Depression, Chronic Pain, and Disability in Primary Care
Arnow, B. A., Hunkeler, E. M., Blasey, C. M., Lee, J., Constantino, M. J., FIREMAN, B. H., KRAEMER, H. C., Dea, R., Robinson, R., & Hayward, C. (2006) · Psychosomatic Medicine · doi:10.1097/01.psy.0000204851.15499.fc · Cited by 542
Treating Depression in Predominantly Low-Income Young Minority Women
Miranda, J. M., Chung, J. Y., Green, B. L., KRUPNICK, J. L., Siddique, J., Revicki, D. A., & Belin, T. (2003) · JAMA · doi:10.1001/jama.290.1.57 · Cited by 531
Homework assignments in cognitive and behavioral therapy: a meta-analysis
Kazantzis, N., Deane, F. P., & Ronan, K. R. (2000) · Clinical Psychology: Science and Practice · doi:10.1093/clipsy.7.2.189 · Cited by 412
Melfi, C. A., Chawla, A. J., Croghan, T. W., Hanna, M. P., Kennedy, S., & Sredl, K. (1998) · Archives of General Psychiatry · doi:10.1001/archpsyc.55.12.1128 · Cited by 409
Mobile Therapy: Case Study Evaluations of a Cell Phone Application for Emotional Self-Awareness
Morris, M. E., Kathawala, Q., Leen, T. K., Gorenstein, E. E., Guilak, F., Labhard, M., & Deleeuw, W. (2010) · Journal of Medical Internet Research · doi:10.2196/jmir.1371 · Cited by 384
Gaps in Service Utilization by Mexican Americans With Mental Health Problems
Vega, W. A., Kolody, B., Aguilar-Gaxiola, S., & Catalano, R. (1999) · American Journal of Psychiatry · doi:10.1176/ajp.156.6.928 · Cited by 354
The use of text messaging to improve attendance in primary care: a randomized controlled trial
Leong, K. C., Chen, W. S., Leong, K. W., Mastura, I., Mimi, O., Sheikh, M. A., Zailinawati, A. H., Ng, C. J., Phua, K. L., & Teng, C. L. (2006) · Family Practice · doi:10.1093/fampra/cml044 · Cited by 291
Using evidence-based internet interventions to reduce health disparities worldwide.
Muñoz, R. F. (2010) · Journal of Medical Internet Research · doi:10.2196/jmir.1463 · Cited by 242
Self-citationImproved Adherence and Outcomes for Pediatric Liver Transplant Recipients by Using Text Messaging
Miloh, T., Annunziato, R. A., Arnon, R., Warshaw, J. K., Parkar, S., Suchy, F. J., Iyer, K. R., & Kerkar, N. N. (2009) · PEDIATRICS · doi:10.1542/peds.2009-0415 · Cited by 207
Muñoz, R. F., & Mendelson, T. (2005) · Journal of Consulting and Clinical Psychology · doi:10.1037/0022-006x.73.5.790 · Cited by 185
Self-citationBryant, M. J., Simons, A. D., & Thase, M. E. (1999) · Cognitive Therapy and Research · doi:10.1023/a:1018703901116 · Cited by 183
Organista, K. C., Muñoz, R. F., & Gonzalez, G. M. (1994) · Cognitive Therapy and Research · doi:10.1007/bf02357778 · Cited by 160
Self-citationUse of text messaging in the aftercare of patients with bulimia nervosa
Bauer, S., Percevic, R., Okon, E., Meermann, R., & Kordy, H. (2003) · European Eating Disorders Review · doi:10.1002/erv.521 · Cited by 148
The use of mobile telephones as adjuncts to cognitive behavioral psychotherapy.
Boschen, M. J., & Casey, L. M. (2008) · Professional Psychology Research and Practice · doi:10.1037/0735-7028.39.5.546 · Cited by 126
A national survey of practicing psychologists’ use and attitudes toward homework in psychotherapy
Kazantzis, N., Lampropoulos, G. K., & Deane, F. P. (2005) · Journal of Consulting and Clinical Psychology · doi:10.1037/0022-006x.73.4.742 · Cited by 112
Practice Makes Progress? Homework Assignments and Outcome in Treatment of Cocaine Dependence.
Carroll, K. M., Nich, C., & Ball, S. A. (2005) · Journal of Consulting and Clinical Psychology · doi:10.1037/0022-006x.73.4.749 · Cited by 75
Predictors of Early Dropout From Psychotherapy for Depression in Community Practice
Simon, G. E., & Ludman, E. J. (2010) · Psychiatric Services · doi:10.1176/ps.2010.61.7.684 · Cited by 75
Psychotherapy Revised: New Frontiers in Research and Practice
Phillips, E. L. (1985) · Medical Entomology and Zoology · Cited by 72
Christensen, A., Miller, W. R., & Muñoz, R. F. (1978) · Professional Psychology · doi:10.1037/0735-7028.9.2.249 · Cited by 55
Self-citationFlynn, H. A. (2010) · Cognitive and Behavioral Practice · doi:10.1016/j.cbpra.2009.09.006 · Cited by 43
Reasons for terminating psychotherapy: a general population study
Westmacott, R. P., & Hunsley, J. D. (2010) · Journal of Clinical Psychology · doi:10.1002/jclp.20702 · Cited by 39
Cited by
Sorted by citations
Mapping mHealth research: a decade of evolution
Fiordelli, M., Diviani, N., & Schulz, P. J. (2013) · Journal of Medical Internet Research · doi:10.2196/jmir.2430 · Cited by 570
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
Berrouiguet, S., Baca-García, E., Brandt, S., Walter, M., & Courtet, P. (2016) · Journal of Medical Internet Research · doi:10.2196/jmir.5066 · Cited by 332
Natural language processing in mental health applications using non-clinical texts
Calvo, R. A., Milne, D., Hussain, M. S., & Christensen, H. M. (2017) · Natural Language Engineering · doi:10.1017/s1351324916000383 · Cited by 405
Mobile, social, and wearable computing and the evolution of psychological practice.
Morris, M. E., & Aguilera, A. (2012) · Professional Psychology Research and Practice · doi:10.1037/a0029041 · Cited by 309
Self-citation
Metadata
- Authors
- Aguilera, A., & Muñoz, R. F.
- Affiliations
- San Francisco General Hospital (US)
- Venue
- Professional Psychology: Research and Practice
- Published
- 2011-12
- Volume
- 42
- Issue
- 6
- Pages
- 472-478
- ISSN
- 0735-7028 (ISSN-L)
- 1939-1323
- PMC
- PMC4267577
- OpenAlex
- W2019528246
- Cited by
- 159
- References
- 39
- Citations by year
- 2026: 1 · 2025: 7 · 2024: 4 · 2023: 4 · 2022: 8 · 2021: 12 · 2020: 6 · 2019: 11 · 2018: 11 · 2017: 19 · 2016: 21 · 2015: 26 · 2014: 10 · 2013: 12 · 2012: 7
- FWCI
- 12.41
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Professional Psychology Research and Practice (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institute of Mental Health (K23MH094442)
- National Institute on Minority Health and Health Disparities (L60 MD003465)
- Topics
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Telemedicine and Telehealth Implementation
- Keywords
- text messaging, cognitive behavioral therapy, depression, low-income populations, homework adherence, self-monitoring, mood tracking, automated intervention, Spanish-language intervention
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