ArticleJMIR mental health2016
Automated Remote Monitoring of Depression: Acceptance Among Low-Income Patients in Diabetes Disease Management.
Article in JMIR mental health, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT01781013 (Care Management Technology to Facilitate Depression Care in Safety Net Diabetes Clinics), which is not on this map. Cited by 19 papers.
What it found
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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.
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.
Care Management Technology to Facilitate Depression Care in Safety Net Diabetes Clinics
Who cites it
19 citing papers in PubMed.
- Technology-Facilitated Depression Self-Management Linked with Lay Supporters and Primary Care Clinics: Randomized Controlled Trial in a Low-Income Sample.Telemedicine journal and e-health : the official journal of the American Telemedicine Association · 2022Trial
- Comparative Effectiveness of a Technology-Facilitated Depression Care Management Model in Safety-Net Primary Care Patients With Type 2 Diabetes: 6-Month Outcomes of a Large Clinical Trial.Journal of medical Internet research · 2018Trial
- Factors Affecting Telehealth Consultation in Diabetic Patients: A Systematic Scoping Review.International journal of telemedicine and applications · 2026Review
- Application of a Sociotechnical Framework to Uncover Factors That Influence Effective User Engagement With Digital Mental Health Tools in Clinical Care Contexts: Scoping Review.Journal of medical Internet research · 2025Article
- A decision-analytic method to evaluate the cost-effectiveness of remote monitoring technology for chronic depression.International journal of technology assessment in health care · 2025Article
- Technology-Supported Integrated Care Innovations to Support Diabetes and Mental Health Care: Scoping Review.JMIR diabetes · 2023Article
- Digital Health Interventions for Depression and Anxiety Among People With Chronic Conditions: Scoping Review.Journal of medical Internet research · 2022Article
- Digital and Mobile Health Technology in Collaborative Behavioral Health Care: Scoping Review.JMIR mental health · 2022Article
- Harnessing Digital Health Technologies to Remotely Manage Diabetic Foot Syndrome: A Narrative Review.Medicina (Kaunas, Lithuania) · 2021Review
- Assessment of Psychological Distress in Adults With Type 2 Diabetes Mellitus Through Technologies: Literature Review.Journal of medical Internet research · 2021Review
- Comparison of Satisfaction With Comorbid Depression Care Models Among Low-Income Patients With Diabetes.Journal of patient experience · 2020Article
- A Digital Library for Increasing Awareness About Living Donor Kidney Transplants: Formative Study.JMIR formative research · 2020Article
- Text Messaging as a Screening Tool for Depression and Related Conditions in Underserved, Predominantly Minority Safety Net Primary Care Patients: Validity Study.Journal of medical Internet research · 2020Article
- Use of Patient-Reported Data to Match Depression Screening Intervals With Depression Risk Profiles in Primary Care Patients With Diabetes: Development and Validation of Prediction Models for Major Depression.JMIR formative research · 2019Article
- Screening Depression and Related Conditions via Text Messaging Versus Interview Assessment: Protocol for a Randomized Study.JMIR research protocols · 2019Article
- Assessment of Health Information Technology Interventions in Evidence-Based Medicine: A Systematic Review by Adopting a Methodological Evaluation Framework.Healthcare (Basel, Switzerland) · 2018Review
- Cost-Effectiveness of a Technology-Facilitated Depression Care Management Adoption Model in Safety-Net Primary Care Patients with Type 2 Diabetes.Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research · 2018Article
- Article
- Acceptability of mHealth augmentation of Collaborative Care: A mixed methods pilot study.General hospital psychiatryArticle
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundRemote patient monitoring is increasingly integrated into health care delivery to expand access and increase effectiveness. Automation can add efficiency to remote monitoring, but patient acceptance of automated tools is critical for success. From 2010 to 2013, the Diabetes-Depression Care-management Adoption Trial (DCAT)-a quasi-experimental comparative effectiveness research trial aimed at accelerating the adoption of collaborative depression care in a safety-net health care system-tested a fully automated telephonic assessment (ATA) depression monitoring system serving low-income patients with diabetes.
objectiveThe aim of this study was to determine patient acceptance of ATA calls over time, and to identify factors predicting long-term patient acceptance of ATA calls.
methodsWe conducted two analyses using data from the DCAT technology-facilitated care arm, in which for 12 months the ATA system periodically assessed depression symptoms, monitored treatment adherence, prompted self-care behaviors, and inquired about patients' needs for provider contact. Patients received assessments at 6, 12, and 18 months using Likert-scale measures of willingness to use ATA calls, preferred mode of reach, perceived ease of use, usefulness, nonintrusiveness, privacy/security, and long-term usefulness. For the first analysis (patient acceptance over time), we computed descriptive statistics of these measures. In the second analysis (predictive factors), we collapsed patients into two groups: those reporting "high" versus "low" willingness to use ATA calls. To compare them, we used independent t tests for continuous variables and Pearson chi-square tests for categorical variables. Next, we jointly entered independent factors found to be significantly associated with 18-month willingness to use ATA calls at the univariate level into a logistic regression model with backward selection to identify predictive factors. We performed a final logistic regression model with the identified significant predictive factors and reported the odds ratio estimates and 95% confidence intervals.
resultsAt 6 and 12 months, respectively, 89.6% (69/77) and 63.7% (49/77) of patients "agreed" or "strongly agreed" that they would be willing to use ATA calls in the future. At 18 months, 51.0% (64/125) of patients perceived ATA calls as useful and 59.7% (46/77) were willing to use the technology. Moreover, in the first 6 months, most patients reported that ATA calls felt private/secure (75.9%, 82/108) and were easy to use (86.2%, 94/109), useful (65.1%, 71/109), and nonintrusive (87.2%, 95/109). Perceived usefulness, however, decreased to 54.1% (59/109) in the second 6 months of the trial. Factors predicting willingness to use ATA calls at the 18-month follow-up were perceived privacy/security and long-term perceived usefulness of ATA calls. No patient characteristics were significant predictors of long-term acceptance.
conclusionsIn the short term, patients are generally accepting of ATA calls for depression monitoring, with ATA call design and the care management intervention being primary factors influencing patient acceptance. Acceptance over the long term requires that the system be perceived as private/secure, and that it be constantly useful for patients' needs of awareness of feelings, self-care reminders, and connectivity with health care providers.
trial registrationClinicalTrials.gov NCT01781013; https://clinicaltrials.gov/ct2/show/NCT01781013 (Archived by WebCite at http://www.webcitation.org/6e7NGku56).
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