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Behavioral Motivation Support Versus Personalized Dietary Management for Metabolic and Behavioral Outcomes in MASLD: A Network Meta-Analysis

Submitted:

01 May 2026

Posted:

07 May 2026

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Abstract
Background: MASLD has a prevalence of almost one-third in adults worldwide and is not currently treated pharmacologically with a first-line therapy. Lifestyle change is still the foundation of management, however, the relative effectiveness of various behavioral and dietary intervention approaches is poorly defined in both metabolic and psychobehavioral outcome areas. Objective: We compared four classes of interventions, behavioral motivation support (BMS), biomarker-guided personalized diet management (BPDM), general diet education (GDE), and prescribed diet models (PDM) against usual care (UC) in patients with MASLD using network meta-analysis (NMA). Methods: Six electronic databases and two trial registerswere searched through 31 March 2026. Eligible studies were randomized controlled trials (RCTs) in adults with MASLD/NAFLD; risk of bias was assessed with the Cochrane ROB 2 tool, and evidence certainty was graded using the CINeMA-informed GRADE framework. A frequentist random-effects NMA was conducted using the R package netmeta; interventions were ranked by P-scores. Results: Fourteen RCTs (n = 1,805; published 2016–2026) were included. BMS showed the largest ALT reduction (MD −15.63 U/L, 95% CI −27.56 to −3.69; P-score 0.89) and ranked highest for dietary behavior and self-efficacy outcomes. BPDM ranked first for BMI (MD −1.84 kg/m², 95% CI −3.48 to −0.20; P-score 0.82), body weight (MD −5.80 kg; P-score 0.76), and HbA1c improvement (P-score 0.75). All certainty ratings were very low. Conclusions: These findings suggest that BMS and BPDM may target complementary outcome domains in MASLD; however, all estimates carry very low certainty, and adequately powered direct comparative trials are essential before clinical translation.
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Copyright: This open access article is published under a Creative Commons CC BY 4.0 license, which permit the free download, distribution, and reuse, provided that the author and preprint are cited in any reuse.
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