ReviewmHealth2016
Connected health: a review of the literature.
Review in mHealth, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
8 citing papers in PubMed.
- A randomized controlled trial to evaluate a behavioral economic strategy for improving mobility in veterans with chronic pain.PloS one · 2021Trial
- The Extent and Coverage of Current Knowledge of Connected Health: Systematic Mapping Study.Journal of medical Internet research · 2019Review
- Connected Health Services: Framework for an Impact Assessment.Journal of medical Internet research · 2019Article
- Accelerating Research With Technology: Rapid Recruitment for a Large-Scale Web-Based Sleep Study.JMIR research protocols · 2019Article
- Rethinking the Endpoints of mHealth Intervention Research in Diabetes Care.Journal of diabetes science and technology · 2018Article
- Participatory Technology Development to Enhance Community Resilience.Ethnicity & disease · 2018Article
- Diabetes Data Management System to Improve Glycemic Control in People With Type 1 Diabetes: Prospective Cohort Study.JMIR mHealth and uHealth · 2017Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The presence of social support, and more recently, connection, has been linked to multiple health benefits and longevity measures and the lack of connection is associated with premature morbidity and mortality. Connected health is a growing industry, and we were interested in determining whether or not scholars in the field have established the ways in which technology could facilitate or promote connection between patients and healthcare providers. This integrative literature review sought to collect and analyze research studies addressing social support or connection in a sample of patients with diabetes to evaluate the social support or connection metrics in use, the type of technology deployed by researchers to achieve connection, and to assess the state of the science in this area. We hypothesized that being connected to someone who cares is good for your health. We believe this holds true even when connection is accomplished with mobile technologies. Thirty five studies were included in this review, 21 utilized technology to enhance patient-provider connection. The articles included in this review were from a total of more than nine countries and took place in hospital, physician office, and community settings. They represented people from childhood through to old age. Technologies evaluated include: telephone interventions, email, text messaging, interactive voice response (IVR), video blogs, apps, websites, and social media. There were multiple operational definitions of social support and self-management used as variables within the studies. Findings from this review suggest that being connected does matter to patients with diabetes, and being connected to family matters the most, even though the associations are complex and not always predictable. Furthermore, patients with diabetes will utilize a variety of technologies to connect with healthcare providers, team members, and even other people with the same disease. The use of technology with diabetes patients positively impacts a variety of health outcomes, such as HbA1c, weight, physical activity, healthy eating, cholesterol and frequency of glycemic monitoring.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.