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Background/objectives: One of the main challenges in weight loss is the dramatic interindividual variability in response to treatment. We aim to systematically identify factors relevant to weight loss effectiveness using machine learning (ML).
Subjects/methods: We studied 1810 participants in the ONTIME program, which is based on cognitive-behavioral therapy for obesity (CBT-OB). We assessed 138 variables representing participants' characteristics, clinical history, metabolic status, dietary intake, physical activity, sleep habits, chronotype, emotional eating, and social and environmental barriers to losing weight. We used XGBoost (extreme gradient boosting) to predict treatment response and SHAP (SHapley Additive exPlanations) to identify the most relevant factors for weight loss effectiveness.
Results: The total weight loss was 8.45% of the initial weight, the rate of weight loss was 543 g/wk., and attrition was 33%. Treatment duration (mean ± SD: 14.33 ± 8.61 weeks) and initial BMI (28.9 ± 3.33) were crucial factors for all three outcomes. The lack of motivation emerged as the most significant barrier to total weight loss and also influenced the rate of weight loss and attrition. Participants who maintained their motivation lost 1.4% more of their initial body weight than those who lost motivation during treatment (P < 0.0001). The second and third critical factors for decreased total weight loss were lower "self-monitoring" and "eating habits during treatment" (particularly higher snacking). Higher physical activity was a key variable for the greater rate of weight loss.
Conclusions: Machine learning analysis revealed key modifiable lifestyle factors during treatment, highlighting avenues for targeted interventions in future weight loss programs. Specifically, interventions should prioritize strategies to sustain motivation, address snacking behaviors, and enhance self-monitoring techniques. Further research is warranted to evaluate the efficacy of these strategies in improving weight loss outcomes.
Trial Registration: clinicaltrials.gov: NCT02829619.
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http://dx.doi.org/10.1038/s41366-025-01766-w | DOI Listing |
Int J Nurs Knowl
September 2025
Luciano Feijão College, Sobral, Ceará, Brazil.
Purpose: To clinically validate the nursing diagnosis "Inadequate Nutritional Intake" based on elements identified within a specific situation theory framework in the context of children with cancer.
Methods: This is a diagnostic accuracy study following the Standards for Reporting Diagnostic Accuracy Studies (STARD) protocol. Specifically, it refers to the clinical validation phase of the nursing diagnosis Inadequate nutritional intake, using a cross-sectional design.
Obes Surg
September 2025
Faculty of Health Sciences & Medicine, Bond University, Gold Coast, Australia.
This rapid systematic review aimed to evaluate the diagnostic accuracy (concurrent validity, predictive ability, reliability) of indirect calorimetry (IC) for measuring resting energy expenditure (REE) in adults with overweight or obesity. PubMed and Web of Science searched for studies measuring REE by IC in adults with overweight or obesity and reported primary outcomes: concurrent validity, predictive ability, or reliability. N = 22 studies were included that evaluated n = 10 IC devices.
View Article and Find Full Text PDFBioresour Technol
September 2025
State Key Laboratory of Coal Combustion, School of Energy and Power Engineering, Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan 430074, China.
The pyrolysis of flue-cured tobacco stalks (TS) faces challenges such as low bio-oil value and utilization efficiency. Existing studies have overlooked the anatomical heterogeneity of tobacco stalks, thereby limiting the directional regulation of high-value components, such as nicotine and phenolic compounds. This study divides TS into the husk (TSH), xylem (TSX), and pith (TSP), and investigates their physicochemical properties, pyrolysis behavior (through TGA and fixed-bed pyrolysis experiments), and interactions.
View Article and Find Full Text PDFPhysiol Behav
September 2025
Department of Psychiatry, Icahn School of Medicine at Mount Sinai, 1399 Park Avenue, New York, NY, 10029, United States. Electronic address:
Sleeve gastrectomy (SG) and Roux-en-Y gastric bypass (RYGB) are the most effective weight loss procedures for severe obesity. However, there is recent evidence of increased alcohol intake and new onset alcohol use disorder (AUD) by 2 yr following both operations. Although the two surgeries differ anatomically, they lead to similar increased drinking.
View Article and Find Full Text PDFEnviron Pollut
September 2025
Centre for Environmental and Marine Studies (CESAM) & Department of Biology, University of Aveiro, Portugal. Electronic address:
Printed circuit boards (PCB) present a complex recycling challenge due to their miniaturisation and different constituents (e.g., metals, plastics), highlighting the need for integrated bioprocessing approaches.
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