Trial reportThe international journal of behavioral nutrition and physical activity2016
Improved eating behaviours mediate weight gain prevention of young adults: moderation and mediation results of a randomised controlled trial of TXT2BFiT, mHealth program.
Trial report in The international journal of behavioral nutrition and physical activity, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 9 of them syntheses that pooled it.
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Who cites it
21 citing papers in PubMed, 9 syntheses or guidelines pooled it, 40 citations in OpenAlex.
- Effect of Digital Health Interventions on College Students' Lifestyle Behaviors: Systematic Review.Journal of medical Internet research · 2026Pooled it
- Effectiveness of booster strategies to promote physical activity maintenance: a systematic review and meta-analysis.The international journal of behavioral nutrition and physical activity · 2025Pooled it
- Mobile health (m-health) smartphone interventions for adolescents and adults with overweight or obesity.The Cochrane database of systematic reviews · 2024Pooled it
- Mobile Health Interventions and RCTs: Structured Taxonomy and Research Framework.Journal of medical systems · 2022Pooled it
- The Effectiveness of Nutritional Education Interventions on Dietary Intake in Young Black Males: A Near-Empty Systematic Review.Nutrients · 2022Pooled it
- Pooled it
- Digital Interventions on Healthy Lifestyle Management: Systematic Review.Journal of medical Internet research · 2021Pooled it
- Human Coaching Methodologies for Automatic Electronic Coaching (eCoaching) as Behavioral Interventions With Information and Communication Technology: Systematic Review.Journal of medical Internet research · 2021Pooled it
- The Relationship between Vegetable Intake and Weight Outcomes: A Systematic Review of Cohort Studies.Nutrients · 2018Pooled it
- Factors associated with weight gain prevention in young adults with serious mental illness.Early intervention in psychiatry · 2023Trial
- Baseline Psychosocial and Demographic Factors Associated with Study Attrition and 12-Month Weight Gain in the DIETFITS Trial.Obesity (Silver Spring, Md.) · 2019Trial
- Diet Quality in a Weight Gain Prevention Trial of Reproductive Aged Women: A Secondary Analysis of a Cluster Randomized Controlled Trial.Nutrients · 2018Trial
- Mediators of two selective prevention interventions targeting both obesity and eating disorders.Behaviour research and therapy · 2018Trial
- Nutrition and physical activity interventions for the general population with and without cardiometabolic risk: a scoping review.Public health nutrition · 2021Article
- Prediction of the Influential Factors on Eating Behaviors: A Hybrid Model of Structural Equation Modelling-Artificial Neural Networks.TheScientificWorldJournal · 2020Article
- Image-Based Dietary Assessment and Tailored Feedback Using Mobile Technology: Mediating Behavior Change in Young Adults.Nutrients · 2019Article
- Good intentions are not enough: how informatics interventions can worsen inequality.Journal of the American Medical Informatics Association : JAMIA · 2018Article
- Causal Analysis of Self-tracked Time Series Data Using a Counterfactual Framework for N-of-1 Trials.Methods of information in medicine · 2018Article
- Social Determinants and Poor Diet Quality of Energy-Dense Diets of Australian Young Adults.Healthcare (Basel, Switzerland) · 2017Article
- The fruit and vegetable intake of young Australian adults: a population perspective.Public health nutrition · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundExplanatory evaluation of interventions for prevention of weight gain is required beyond changes in weight, to determine for whom the intervention works and the underlying mechanisms of change. It was hypothesised that participant characteristics moderate intervention effect on weight change and improved eating and physical activity behaviours during the 3-month program mediate the relationship between intervention and weight.
methodsIn our randomised controlled trial, young adults at risk of weight gain (n = 250) were assigned either to an intervention group that received a 3-month mHealth (TXT2BFiT) program with 6-month maintenance or to a control group. Data were collected via online self-report surveys. Hypothesised moderators and mediators of the intervention effect on weight were independently assessed in PROCESS macro models for 3 and 9-month weight change.
resultsMales (P = 0.01), mid-20s age group (P = 0.04), and higher income earners (P = 0.02) moderated intervention effects on weight change at 3-months and males only at 9-months (P = 0.02). Weight change at 3 (-1.12 kg) and 9-months (-1.38 kg) remained significant when 3-month nutrition and physical activity behaviours were specified as mediators (P <0.01 and P = 0.01 respectively). Indirect paths explained 39% (0.72/1.85 kg) and 40 % (0.92/2.3 kg) of total effect on weight change at 3 and 9-months respectively. Increased vegetable intake by intervention group at 3-months accounted for 19 and 17% and decreased sugar-sweetened beverages accounted for 8 and 13% of indirect weight change effects at 3 and 9-months respectively.
conclusionsTXT2BFiT was effective for both young men and women. Small sustained behavioural changes, including increased vegetable intake and decreased sugar-sweetened beverages consumption significantly mediated the intervention's effects on weight change. Improved eating behaviours and increased physical activity accounted for approximately 40% of the weight change.
trial registrationThe trial is registered with the Australian New Zealand Clinical Trials Registry ( ACTRN12612000924853 ).
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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.