ArticlePloS one2022
A feasibility study to test a novel approach to dietary weight loss with a focus on assisting informed decision making in food selection.
Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 3 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.
Comparison of Coping Strategies to Reduce Food Cravings During Dietary Weight Loss
Testing an Online Dietary Weight Loss Program for Arab Adults: A Comparative Study With Existing Hospital-Based Weight Loss Interventions in Saudi Arabia
Who cites it
3 citing papers in PubMed.
- A Novel Web App for Dietary Weight Management: Development, Implementation, and Usability Study.JMIR formative research · 2024Article
- Successful dietary changes correlate with weight-loss outcomes in a new dietary weight-loss program.Obesity science & practice · 2024Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
Obesity is a significant contributor to the development of chronic diseases, some of which can be prevented or reversed by weight loss. However, dietary weight loss programs have shortcomings in the success rate, magnitude, or sustainability of weight loss. The Individualized Diet Improvement Program's (iDip) objective was to test the feasibility of a novel approach that helps individuals self-select a sustainable diet for weight loss and maintenance instead of providing weight loss products or rigid diet instructions to follow. The iDip study consisted of 22 dietary improvement sessions over 12 months with six months of follow-up. Daily weights were collected, and a chart summarizing progress was provided weekly. Six 24-hour dietary records were collected, and dietary feedback was provided in the form of a protein-fiber plot, in which protein/energy and fiber/energy of foods were plotted two-dimensionally together with a target box specific to weight loss or maintenance. An exit survey was conducted at 12 months. Twelve (nine female, 46.3±3.1 years (mean±SE)) of the initial 14 participants (BMI>28 kg/m2) completed all sessions. Mean percent weight loss (n = 12) at six and 12 months was -4.9%±1.1 (p = 0.001) and -5.4%±1.7 (p = 0.007), respectively. Weight loss varied among individuals at 12 months; top and bottom halves (n = 6 each) achieved -9.7%±1.7 (p = 0.0008) and -1.0%±1.4 weight loss, respectively. The 24-hour records showed a significant increase in protein density from baseline to final (4.1g/100kcal±0.3 vs. 5.7g/100kcal±0.5; p = 0.008). Although mean fiber density showed no significant change from the first month (1.3g/100kcal±0.1), the top half had significantly higher fiber/energy intake than the bottom half group. The survey suggested that all participants valued the program and its self-guided diet approach. In conclusion, half of the participants successfully lost >5% and maintained the lost weight for 12 months without strict diet instructions, showing the feasibility of the informed decision-making approach.
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.