ArticleDigital health
Using self-monitoring technology for nutritional counseling and weight management.
Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 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
16 citing papers in PubMed, 22 citations in OpenAlex.
- Coach access to digital self-monitoring data: an experimental test of short-term effects in behavioral weight-loss treatment.Obesity (Silver Spring, Md.) · 2024Trial
- Hypothalamic obesity in pediatric vs. adult craniopharyngioma: mechanisms, management, and cardiometabolic outcomes.Pituitary · 2026Review
- Within-Day Patterns of Self-Monitoring Dietary Intake and Weight Loss in a Behavioral Weight Management Program.Obesity science & practice · 2026Article
- Article
- Participant food tracking in psychiatric ketogenic metabolic therapy: an unresolved clinical, psychosocial, and implementation question.Frontiers in nutrition · 2026Review
- Digital communication tools used to promote healthy lifestyles: an overview of reviews from the BRIDGE project.Frontiers in digital health · 2026Review
- Behavioral Change Intervention to Promote a Healthier Postpartum Lifestyle: Mixed Methods Pilot Study.JMIR formative research · 2025Article
- Evaluating the RESET care program: Advancing towards scalable and effective healthcare solutions for metabolic dysfunction-associated liver disease.World journal of hepatology · 2025Article
- Barriers and facilitators to non-pharmacological management of metabolic dysfunction-associated steatotic liver disease: a qualitative evidence synthesis.Frontiers in pharmacology · 2025Review
- The Efficacy of Telehealth Versus In-Person Management Delivery in Adult Patients with Obesity.Healthcare (Basel, Switzerland) · 2024Article
- Psychological and behavioral responses to daily weight gain during behavioral weight loss treatment.Journal of behavioral medicine · 2024Article
- MyTrack+: Human-centered design of an mHealth app to support long-term weight loss maintenance.Frontiers in digital health · 2024Article
- A survey on the awareness, current management, and barriers for non-alcoholic fatty liver disease among the general Korean population.Scientific reports · 2023Article
- The Effectiveness of Wearable Devices in Non-Communicable Diseases to Manage Physical Activity and Nutrition: Where We Are?Nutrients · 2023Review
- The Effects of Providing a Connected Scale in an App-Based Digital Health Program: Cross-sectional Examination.JMIR mHealth and uHealth · 2023Article
- What Intervention Elements Drive Weight Loss in Blended-Care Behavior Change Interventions? A Real-World Data Analysis with 25,706 Patients.Nutrients · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
Self-monitoring of weight, dietary intake, and physical activity is a key strategy for weight management in adults with obesity. Despite research suggesting consistent associations between more frequent self-monitoring and greater success with weight regulation, adherence is often suboptimal and tends to decrease over time. New technologies such as smartphone applications, e-scales, and wearable devices can help eliminate some of the barriers individuals experience with traditional self-monitoring tools, and research has demonstrated that these tools may improve self-monitoring adherence. To improve the integration of these tools in clinical practice, the current narrative review introduces the various types of self-monitoring technologies, presents current evidence regarding their use for nutrition support and weight management, and provides guidance for optimal implementation. The review ends with a discussion of barriers to the implementation of these technologies and the role that they should optimally play in nutritional counseling and weight management. Although newer self-monitoring technologies may help improve adherence to self-monitoring, these tools should not be viewed as an intervention in and of themselves and are most efficacious when implemented with ongoing clinical support.
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.