Effects of a Telenutrition Weight Loss Program Supported with Telemonitoring and Telehealth Coaching on Anthropometric and Biochemical Measures in Overweight and Obese Adults: A Pilot Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND/OBJECTIVES: Telenutrition has been reported to enable dietitians to support outpatients remotely in an accessible and convenient state. The literature shows that both telemonitoring and health coaching are effective approaches for achieving a greater impact on weight loss and the client's compliance with their diet. The purpose of the present study was to assess the impact of a telenutrition weight loss program on weight reduction, supported with telemonitoring and health coaching. METHODS: A pilot randomized controlled trial was conducted among overweight and obese adults. The control group (n = 11) received a hypocaloric and tailored diet via telenutrition. The intervention group (n = 18) also received a hypocaloric and tailored diet via telenutrition, but it was supported with weekly telemonitoring and monthly telehealth coaching. RESULTS: Participants who joined the intervention group showed a reduction in weight, BMI, fat %, visceral fat, and WC, whereas participants in the control group only displayed a reduction in WC after a period of 3 months. Comparing between the groups, a greater reduction in weight, BMI, fat %, and visceral fat was seen in the intervention group. Furthermore, muscle % was significantly higher in the intervention group after a period of 3 months. At the 6-month follow-up, the intervention group still showed promising results, but they were not significant. CONCLUSIONS: Our data indicate that the integration of the three approaches of telenutrition, telemonitoring, and health coaching in dietary weight loss programs can have significant impacts on weight loss in obese and overweight individuals.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".